MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care

By Tina Hernandez-Boussard, S. Bozkurt, John P. A. Ioannidis, Nigam H. Shah. J. Am. Medical Informatics Assoc., 2020

333 citations recorded by the source corpus.

Abstract The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Information for Medical AI Reporting), a proposal describing the minimum information necessary to understand intended predictions, target populations, and hidden biases, and the ability to generalize these emerging technologies. We call for a standard to accurately and responsibly report on AI in health care. This will facilitate the design and implementation of these models and promote the development and use of associated clinical decision support tools, as well as manage concerns regarding accuracy and bias.

Subfields: Artificial Intelligence, Health Informatics, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/a53b798078e9f94e0059a34eb7c5078c054887c0

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